The MA plots show the log2 fold change (y-axis) versus the mean expression (x-axis) for each gene in the comparison between a condition and the control. Genes are colored based on their differential expression status, which is determined by the user-specified log2 fold change and p-value cutoffs. Significance filtering criteria:
The PCA plot visualizes the principal components of the normalized gene expression data. Each point represents a sample, and samples are colored by their condition. The plot helps to identify patterns and clustering of samples based on their gene expression profiles.The data has been normalized using the vst method before applying PCA.
The table below summarizes the number of differentially expressed genes for each comparison between a condition and the control. Genes are considered differentially expressed if they meet the user-specified fold change and p-value cutoffs. Significance filtering criteria:
The volcano plots show the negative log10 p-value (y-axis) versus the log2 transformed fold change (x-axis) for each gene in the comparison between a condition and the control. Genes are colored based on their differential expression status, which is determined by the user-specified fold change and p-value cutoffs. Significance filtering criteria:
The accompanying summary tables provide the list of upregulated and downregulated genes based on the specified cutoffs, along with their base mean expression, log2 fold change, and p-value.
The heatmap displays the normalized expression values for the top 50 genes with the highest variance across samples. Genes (rows) and samples (columns) are clustered based on their expression patterns, helping to identify groups of genes with similar expression profiles and groups of samples with similar gene expression. The data has been normalized using the vst method before generating the heatmap. The color scale represents the normalized expression values, with darker colors indicating higher expression and lighter colors indicating lower expression.